Inferences

Evaluating inferences is a central skill in logical reasoning. An inference is a conclusion drawn from given facts or statements. For examination-style passages, you must determine whether an inference is directly supported by the passage, requires an additional assumption, contradicts the passage, or is indeterminate from the given information.

• To evaluate an inference, first check whether it can be decided directly from the passage. See if the inference is explicitly supported or contradicted by some sentence or clear implication in the passage.
• If the inference cannot be decided directly from the passage, check whether an additional assumption makes it justifiable or refutable. The extra assumption must be reasonable and universally acceptable in the context of the passage.
• Evaluate the inference with the help of key words used in the passage; words such as all, none, always, never, some, may, must, and could affect the force of an inference.
• To distinguish between "definitely true" and "probably true", check whether the extra assumption (if needed) is universally true in the passage context. Use the same test to distinguish between "definitely false" and "probably false".
• To decide between "probably true" and "data inadequate", ask whether you can reasonably make an extra assumption that supports the inference. If you can, treat it as "probably true". Apply the same logic to differentiate between "probably false" and "data inadequate".

Directions (Q. 1-50): Below is given a passage followed by several possible inferences which can be drawn from the facts stated in the passage? You have to examine each inference separately in the context of the passage and decide upon its degree of truth or falsity. Mark the answer.

1) if the inference is "definitely true", i.e. it properly follows from the statement of facts given.

2) if the inference is "probably true" though not "definitely true" in the light of the facts given.

3) if the inference is "probably false" though not "definitely false" in the light of the facts given.

4) if the inference is "definitely false", i.e. it cannot possibly be drawn from the facts given for it contradicts the given facts.

Statement (1-5):

In India, we are still struggling with elementary problems of healthcare. Our performance in health-related sectors like provision of drinking water, sanitation, education and nutrition remain poor. The healthcare system itself is extremely inadequate and particularly missing at the village level. As our bureaucrats systematically decimated the Community Health Worker (CHW) programme, we face an unenviable prospect of facing the old and new health challenges without infrastructure at the grassroots. Ironically, in the name of infrastructure, various Indian states are busy building tertiary institutes - hospitals - on World Bank loans. Aid agencies are also pushing one program after another, overlooking the absence of adequate infrastructure at the village level. Unfortunately, no one talks of facilities at the village level.

• 1. Other countries have made rapid progress in elementary problems of healthcare by now.
• 2. The basic problem of India's health scenario is the lack of adequate infrastructure at the grass root level.
• 3. Building new hospitals does not add to the existing infrastructure in healthcare.
• 4. The problem of adequate infrastructure is as much in the cities as in the villages.
• 5. Aid agencies are overburdened with programmes and so are not particularly interested in solving any one of them.

Statement (6-10):

India has acquired the dubious distinction of having the largest number of diabetes patients in the world. It has been estimated that the numbers in India would far surpass those in China by 2025. Number of diabetics in China was expected to double and reach an estimated 35-million mark by 2025. In contrast, India would have 57 million diabetics, three times its currently estimated number. It has also been found that diabetics are more prone to develop coronary artery disease. Women with diabetes are also seen to develop heart disease at an earlier age.

Diabetes is the leading cause of blindness, renal failure and cardiovascular diseases. The reason for predisposition of Indians to the disease may be both due to genetic factors as well as central obesity in middle-aged people. Studies have shown a three-to-four-fold difference between urban and rural areas, suggesting lifestyle factors. Central obesity in urban population is higher. In developing countries, majority of people with diabetes will be in the age group of 45 to 64. But in developed countries, diabetes will affect people who are above 65 years. Experts here have stressed the need to start preventive measures. For this, steps should be taken that encourage physical activity.

• 6. The country which tops in the world in diabetes cases has 19 million patients of diabetes.
• 7. Cases of blindness, renal failure and cardiovascular diseases in India are the highest in the world.
• 8. To reduce the number of diabetes cases India has neither the required potential nor any comprehensive plan.
• 9. India is a developing country.
• 10. Cases of diabetes in rural areas of India are lower than those in urban areas.

Statement (11-15):

The quest for big money is enticing professionals in some sectors to shift to more lucrative areas. Take engineers, with their salaries moving at the slowest rates it is no wonder that many engineering graduates are switching over to management courses. And over 80% of the students at the IIM in Calcutta are engineers. Says Ramanuj Majumdar, professor of marketing at the institute. "This trend seems to be market-driven since pay packages are more attractive in management." Like engineering, chartered accountancy (CA) too has been witnessing a relatively sluggish growth. This is partly because CAs, who were the phenomenon of the 70s, have been overtaken by the MBAs.

• 11. Engineers are not satisfied with their salaries in India.
• 12. Maximum of management students at IIM in Calcutta are engineering graduates.
• 13. Pay packages are more attractive in management than other jobs.
• 14. CA's are losing their importance because MBAs are available at cheaper salaries.
• 15. An MBA can run an organization better than a CA.

Statement (16-20):

Change has swept over Chambal. Its ravines are no longer dominated by the likes of the big names of yesteryear, like Man Singh, Malkhan Singh, Phoolan Devi or Putli Bai. Those who have taken over are petty criminals in comparison, targeting poor farmers and shopkeepers. Their forte is small-time robbing and kidnapping because they are not strong enough to lay hands on big farmers, who were the targets of the previous generation of Chambal dacoits. Survivors of old generation feel their generation comprised of rebels who fought against injustice and did not exploit the poor.

• 16. The geography of the Chambal ravines has changed.
• 17. Man Singh was an infamous dacoit of the Chambal ravines.
• 18. Criminals do not have any sense of ethics.
• 19. The law-and-order situation has deteriorated in Chambal.
• 20. People do not know the name of contemporary Chambal dacoits.

Statement (21-25):

Coronary heart diseases and strokes are responsible for more than half the deaths in developed countries like US. The prime culprit is the build-up of cholesterol plaques in the arteries. Ironically, cholesterol is an essential substance of cell membranes. Treatment of heart diseases aims at lowering the levels of the harmful content of cholesterol through diet control and drugs.

• 21. Diet control is an important part of the treatment of heart diseases.
• 22. Other than cholesterol, there are no apparent reasons for heart diseases.
• 23. Heart problems lead to a good number of deaths in UK and France.
• 24. Cholesterol is an undesirable part of our body systems.
• 25. If scientists so desired they may accomplish total banishment of cholesterol from our body system.

How to approach these questions: a stepwise method

1. Read the passage carefully and underline key factual claims. Note statistical figures, comparisons, causes, and explicit value-judgements.
2. Read the inference alone and ask: Does this follow directly from the passage, or does it need an extra assumption?
3. If an extra assumption is needed, test whether that assumption is reasonable and universally acceptable given the passage; if not, the correct classification will usually be "data inadequate" (or here, "probably true/false" depending on available options).
4. Look for keywords that change logical scope: all/none/always/never are strong and usually require explicit support; some/may/could are weaker and easier to justify.
5. If the inference contradicts any sentence or explicit implication in the passage, it is "definitely false".
6. If the passage explicitly or unambiguously supports the inference, it is "definitely true".
7. If the passage neither supports nor contradicts the inference but a reasonable assumption makes it plausible, classify it as "probably true" (or "probably false" if a reasonable assumption makes it implausible).

Common clue words and their typical impact

• All / every / always / never / none - Strong universal claims; require explicit passage support.
• Most / majority / usually - Strong but defeasible; may allow "probably true" if passage gives supporting trends.
• Some / a few / may / could / might - Weak claims; often supported by partial evidence or plausible assumptions.
• Leads to / causes / results in - Causal language; check whether passage asserts causation or only correlation.
• Suggest / indicate / may be due to - Tentative language in the passage; inferences using such language are typically weaker and may be "probably true" rather than "definitely true".

Common traps and examiner tactics

• Options that change a word to a universal term ("all", "always") from a weaker claim in the passage are usually incorrect unless passage explicitly uses a universal.
• Introducing facts not mentioned in the passage (e.g., specific numbers, dates, names not present) makes the inference unsupported.
• Confusing correlation with causation: if passage only suggests association, do not infer definite causation.
• Over-extending a generalisation from one subgroup to the whole population is unsafe unless the passage supports it.

Final brief summary

Classify each inference by checking direct support, contradiction, need for reasonable assumptions, and strength of claim using clue words. Prefer literal passage evidence; allow only those additional assumptions that are justifiable and contextually acceptable. Use the fourfold scale-definitely true, probably true, probably false, definitely false-consistently and cautiously.